Tagungsbeiträge

Using Interaction Signals for Job Recommendations

AutorBenjamin Kille, Fabian Abel, Balazs Hidasi, Sahin Albayrak
QuelleInternational Conference on Mobile Computing, Applications, and Services 
LinksBibTeX 

Job recommender systems depend on accurate feedback to improve their suggestions. Implicit feedback arises in terms of clicks, bookmarks and replies. We present results from a member inquiry conducted on a large-scale job portal. We analyse correlations between ratings and implicit signals to detect situations where members liked their suggestions. Results show that replies and bookmarks reflect preferences much better than clicks.